System for automated real time monitoring of invisible non-productive time of drilling and completion operations for oil wells

Abstract

A monitoring system for drilling and completion of oil wells includes computer equipment with a local server, which collects information from a series of sensors installed in each drilling equipment such as hook load, pressure, depth, flow, RPM and torque sensors, these sensors provide real-time data on the progress and depth of the well. In addition to being stored on the local server, the information is sent to a database in the AWS cloud for replication on a central server. The system allows continuous monitoring of activities both at the drilling site and remotely, which facilitates the optimization of operations and the implementation of improvement plans. The system is also configured to perform calculations of time spent on each activity, pipe connections, drilling speed and pipe travel speed. It also calculates the time lost in each activity based on standard values, generating alarms when established thresholds are exceeded or below defined speeds or other operating metrics. These alarms are transmitted to the driller in real time via a Tablet device, allowing to seek the optimization of the current activity at the moment by means of predictive indications.

Description

FIELD OF THE INVENTION

[0001] The present invention relates to the field of drilling and completion for oil wells. The system is focused on the automation of the operational performance measurement of the operational sequence executed in a well in the drilling and completion stages.

[0002] It stands out in performance management and KPI (Key Performance Indicator) tracking, for the detection and mitigation of invisible non-productive times, allowing to reduce costs and execution times in oil well interventions.BACKGROUND OF THE INVENTION

[0003] In 2019, Pemex Exploración y Producción through the Southwest Marine Region has successfully implemented the Operational Excellence model and work philosophy, which has allowed reducing costs and execution times in well interventions, increasing the number of wells drilled per year and thus the accelerated incorporation of production through the drilling and completion of wells.

[0004] Operational Excellence is a systematized, orderly, standardized work model and scheme with defined indicators, which integrates planning, engineering, design and execution of drilling and completion of wells, based on 3 fundamental objectives:

[0005] 1. Accelerate the incorporation of production through drilling and completion of wells.

[0006] 2. Comply with the production commitments established in the operating programs.

[0007] 3. Reduce costs and execution times in well interventions, which allows increasing the number of wells drilled.

[0008] One of the main components of the Operational Excellence model is the identification of invisible non-productive time. Invisible Non-Productive Time (INPT) is defined as the difference between the actual duration of routine activities and best practices. The INPTs cannot be observed in the conventional reports since they are immersed in the productive times, in order to calculate them it is necessary to measure the times of the activities that generate them, for this purpose, the efficiency is measured by taking the gap between the real performance and the expected performance according to the defined standards.

[0009] As part of the general operational excellence strategy, a methodology was established for the identification and statistical analysis of INPTs in drilling and completion activities.

[0010] Since INPT occurs most frequently at stage changes, personnel with operational experience were assigned to manually measure the activities that generate it such as: drill pipe trips and connections, connections while drilling, assembly and disassembly of downhole assemblies, BOP testing and casing insertion.

[0011] All the information gathered from the operations was captured in a database to quantify the INPTs and thus obtain information records for the analysis, reaching the conclusion that:

[0012] Standardization of the process has not been achieved.

[0013] There was no precise measurement and quantification of invisible times.

[0014] The personnel executing the activity had little participation.

[0015] The Operational Excellence philosophy was not applied in PEMEX.

[0016] The root causes of high changeover times were not well identified.

[0017] There was no knowledge of international standards.

[0018] The improvement criteria were not standardized.

[0019] The parameters were those of the program, which were defined on the basis of statistical times that included malpractice.

[0020] The main causes identified for INPTs in well interventions were analyzed:

[0021] Operational malpractices.

[0022] Crew rotation.

[0023] Inadequate tools.

[0024] Failure to take surveys.

[0025] Prolonged circulation times.

[0026] Lack of personnel.

[0027] Lack of training.

[0028] When working on an oil platform / rig, the driller is responsible for performing multiple functions simultaneously: controlling drilling speed and depth, assessing risks, planning future operations, maintaining constant communication with the rest of the team, managing the time of each activity, and monitoring multiple operations and parameters such as weight, flow, pressure, temperature, tank levels, etc.

[0029] All these activities generate an overload of work and require extreme attention and concentration. To understand how the service assists the driller in activities on a marine or land drilling equipment, it is important to understand that the decision-making process works on the basis of three steps:

[0030] 1. Situational awareness: the ability to recognize indicators, monitor and collect information.

[0031] 2. Comprehension: the ability to understand and interpret something.

[0032] 3. Projection: ability to predict future situations, based on present information.

[0033] In the state of the art there are known systems for monitoring drilling and completion operations for oil wells that make use of various tools for monitoring activities, which are discussed below.

[0034] U.S. Pat. No. 11,286,765 B2, considered the closest prior art, while it collects drilling time data for drilling; converts the drilling time data into segmented drilling time data; decomposes the segmented drilling time data into intrinsic mode functions (IMFs) using an empirical mode decomposition; reconstructs the segmented drilling time data by combining the IMFs with different weightings, thereby producing modified segmented drilling time data; and calculates an invisible lost time for drilling based on the segmented drilling time data and the modified segmented drilling time data; while the data obtained is in real time, unlike the present invention, the drilling time data is converted to segmented drilling parameters for later comparison, with no KPIs being referenced at any time, and no alarms are generated in response to the analyzed data. Although a comparison of data is carried out to calculate the INPT, the processing and variables used are different.

[0035] The document CN 108756848 A focuses on remote automation of drilling technology, while the present invention is concerned only with obtaining and visualizing data in real time, but not with automation or remote control of any kind, only mapping and analysis of information; that is to say, the present invention focuses on optimizing oil well drilling operations, using KPIs, NPTs, and INPTs, maximizing efficiency in critical stages, while the patent application to be compared only focuses on optimizing drilling parameters, without taking into account the time of operations, focusing on the optimization of drilling variables, minimizing costs.

[0036] The method and system for analyzing drilling data described in GB 2552939 A takes data from drilling operations using a system of sensors, which obtain data that are processed in real time to reach conclusions. These conclusions are sent as outputs to support the drilling operation.

[0037] Although both the present invention and the system described in said document are focused on optimizing drilling operations, the present invention distinguishes itself in that it not only uses sensor data (WITS) in real time, but processes it to states, those states are then evaluated as metrics, which in conjunction with the data fed to the system (such as time meters) generate more complex conclusions, and complete reports of all drilling operations optimization information, unlike the patent application to compare which is limited to one output or more.

[0038] GB 2593019 A describes a system that obtains data of the entire drilling operation through the WITS protocol, in addition to having a camera to record the drilling and a drone that captures the entire operation. This system sends information in real time to an offshore team that analyzes the information and can make different decisions depending on their permissions, which are according to their position in the operation, and is validated through authentication.

[0039] Our system, like this one, obtains real-time data through the WITS protocol, but does not obtain visual video records to make decisions, instead, the system processes and then analyzes the data using our KPIs. Our system uses real time data, but it is not analyzed by members of the operation, but processed to states, these states are then evaluated as metrics, which in conjunction with the data fed into the system (such as time meters) generate more complex conclusions, and complete reports of all the drilling operations optimization information, and those conclusions and reports are what are analyzed by the offshore expert personnel, which is a crucial step in the optimization of drilling operations that the patent to be compared does not have.

[0040] U.S. Pat. No. 8,615,660 B1 describes a very complete system using LAN-type connections via radio boxes. All user devices are connected to the LAN, and within the LAN there is a router and a switch, which transmit the data to the satellite receivers. The server can transmit real-time drilling data, well logs, and has an executive dashboard to visualize such data in real time at a remote location.

[0041] While the present invention and the patent application coincide in that they transmit data in real time for the visualization of data from a remote location, our invention is not limited to only carrying out that, but has a system for processing all the data obtained in order to transmit its results in real time. In addition to this, the data collection is different, since in the present invention the WITS protocol is used.

[0042] For this patent application there are too many differentiating factors, since it also does not explicitly mention a reporting system, nor does it have as its main objective to optimize any drilling operation, only to transmit data.

[0043] The patent U.S. Pat. No. 11,365,623 B2 describes a system that receives well data, without explicitly specifying that it is in real time, which are processed and then analyzed and distributed results from the conclusions obtained. It does not emphasize any algorithm to reach such conclusions, but differs from the present invention in that it is not only limited to receiving data from many wells, but also from multiple platforms, such data is processed by means of our data processing tool to obtain data and conclusions to help optimize drilling operations. These conclusions are not distributed, but are displayed within the system's graphical interface.

[0044] Another relevant differential factor is that this patent does not explicitly mention a system for generating reports from the information obtained, unlike our invention.

[0045] Thus, in order to meet the need to improve the efficiency, safety and overall performance of drilling operations, the present invention was developed consisting of hardware, local servers, cloud servers, data processing algorithms and various user interfaces to collect, process, analyze and present relevant information on invisible non-productive times during oil well drilling and completion activities, which is described below.SUMMARY

[0046] The automated monitoring system is designed to detect and mitigate invisible non-productive time during onshore and offshore oil well drilling and completion activities. Its main purpose is to provide accurate, real-time information about the user's position relative to the target, which facilitates safe maneuvers during operations.

[0047] To help the driller in the decision making process, the intention is to implement real-time INPT monitoring, for this a system and automated method is required that is feeding back data in real time during the drilling of the wells, supported by a technological tool called Drillit; this is achieved through the installation of the architecture of this tool through an interactive tablet that has graphical interfaces which trigger instructions and alerts for operators. This increases commitment and provides the driller with better situational awareness (which is a key factor in the decision-making process), allowing for greater concentration during activities.

[0048] The automated system and method with the support of the Drillit tool performs the detection and analysis of the INPTs, which provide all the information needed to perform the activities, this allows the driller to concentrate on a single screen instead of searching for information through multiple platforms or performing these manual calculations. This improves the ability to acquire information and consequently improves the perception of the operation and its ability to monitor and recognize situations of instability and insecurity.

[0049] The system consists of several interconnected components. First, there is a data interface that receives information about the state / status of drilling parameters, this interface collects relevant data, such as block position, drilling speed, pressure and other related parameters.

[0050] The system consists of a tool that runs on a server installed on each drilling platform, this server receives data from the data interface and processes it locally to calculate invisible non-productive time and other important metrics. These metrics provide information on platform performance and help identify potential areas for improvement.

[0051] Data processed on the local server is replicated to a central server in the cloud. At the central server, the data is analyzed using advanced algorithms and techniques to generate new information. This may include non-productive time patterns, performance trends, optimization recommendations for optimization in the drilling operation.

[0052] On the drilling platform, there is a dedicated user interface that allows operators to access real-time information and receive predictive indications of their position relative to the target. There is also a remote user interface that allows users to access the system from external locations via Internet-connected devices.

[0053] In addition, the system includes a user interface to visualize processed information from all connected platforms. This interface allows supervisors and operations managers to get an overview of the performance of multiple platforms and make informed decisions based on the data collected.

[0054] When relevant situations are detected or certain critical thresholds are reached during drilling activities, Drillit can generate automated reports containing updated data and detailed analysis. These reports can include key metrics such as invisible non-productive time, operation efficiency, platform performance, among other relevant indicators.

[0055] Automated real-time reporting allows users to access valuable information quickly and efficiently, without the need for manual analysis or extensive data processing. These automated reports can be customized according to users' needs and preferences, providing specific and relevant information for decision making.

[0056] In addition, automated reports can be easily and quickly shared with team members, supervisors or other stakeholders through different channels, such as email or user interfaces. This facilitates real-time communication and information sharing, which contributes to greater efficiency and collaboration in drilling operations.BRIEF DESCRIPTION OF THE FIGURES

[0057] FIG. 1 shows the ecosystem of the monitoring system.

[0058] FIG. 2 presents a table showing the international KPI standards for each monitored activity.

[0059] FIG. 3 shows a flow chart for the generation of platform states.

[0060] FIG. 4 represents a screenshot of the interface for entering standard parameters.

[0061] FIG. 5 shows a flow chart depicting the process of calculating the INPT according to the present invention.

[0062] FIGS. 6a and 6b represent the codes obtained corresponding to the calculation of the metrics.

[0063] FIG. 7 is a representation of the implementation of the system of the present invention.DETAILED DESCRIPTION OF THE INVENTION

[0064] The present invention relates to an automated monitoring system that is designed to detect and mitigate invisible non-productive time during onshore and offshore oil well drilling and completion activities through a tool called Drillit.

[0065] As can be seen in FIG. 1, the system (1) consists of several interconnected components. There are two administration interfaces; one local and one remote that allow the administrator to interact with the system and generate static data, as well as three visualization interfaces. Two locally installed that are intended to inform both on the drill floor and the driller and a public cloud-based dashboard that can be accessed via the web. First, there is a local server where information about drilling parameters is received and processed.

[0066] Relevant data, such as block position, drilling speed, pressure and other related parameters are collected at this local server by means of a plurality of sensors (2) of the optical, ultrasonic and capacitive type.

[0067] Sensors are located in a variety of locations on the drilling equipment, for example:

[0068] Top drive: Sensors on the top drive collect data on drillstring rotational speed, pulling force and wireline tension.

[0069] Standpipe: Sensors on the standpipe collect data on drilling fluid pressure.

[0070] Pumps: Sensors on the pumps collect data on the flow and pressure of the drilling fluid.

[0071] Winch: Sensors on the winch collect data on cable tension and hoist speed.

[0072] The specific selection and arrangement of sensors allows the Drillit tool to process the data obtained in an accurate and consistent manner, as the information collected is linked to particular and specific properties of the well or platform environment.

[0073] The data obtained in real time by the plurality of sensors (2) are collected using a connection to a TCP IP port using the WITS protocol and sent to the electronic reading room (3), where the WITS server (4) is located.

[0074] By means of a wired connection, the data received in the WITS server (4), are sent to the Drillit server (5) which includes a memory, a processor and the Drillit tool stored in the memory to be executed in the same processor and to be able to carry out the process of comparison and calculation of data corresponding to the detection and analysis of the INPT by means of the combination between real-time data from the sensors and static data, the latter composed of the sequence of operations to be followed by the driller with defined times, sequence of operations and state of operation.

[0075] The data received by WITS protocol, and necessary to perform the processing and calculations are:

[0076] Depth Bit (DBTM): WITS channel that refers to the current depth information of the drill bit.

[0077] Depth Hole (DMEA): WITS channel which refers to the current depth of the hole.

[0078] Block Position (BPOS): WITS channel that refers to the current position of the elevator.

[0079] Rate of Penetration (ROPA): WITS channel which refers to the average bit penetration rate.

[0080] Hookload (HKLA): WITS channel which refers to the average weight of the hook.

[0081] Weight on Bit (WOBA): WITS channel which refers to the average weight on bit during drilling.

[0082] Rotary Torque (TQA): WITS channel which refers to the average surface torque.

[0083] Rotary Speed (RPMA): WITS channel which refers to the average revolutions per minute applied at the surface.

[0084] Standpipe Pressure (SPPA): WITS channel which refers to the average standpipe pressure.

[0085] Mud Flow In (MFIA): WITS channel which refers to the average flowrate or flow.

[0086] The Drillit server (5) is in direct connection with the router (6), which is responsible for wirelessly sending the calculated data information and can be displayed in the operator's cabin (7), to a remote tablet (7a) and / or display (7b), as well as on an on-site display (8), such as the well engineer's office, allowing operators to access the information in real time and receive predictive indications of their position relative to the target. Additionally, the calculated data is sent by the router (6) to an APN (9) (wireless access point), through which all the information that has been monitored and calculated can be sent to the cloud (10) to be displayed through unlimited web access to 24-hour monitoring centers (11) consisting of a plurality of screens and remote interfaces, as well as at external locations (12) consisting of remote interfaces to visualize processed information from all connected platforms, allowing supervisors and operations managers to obtain an overview of the performance of multiple platforms and make informed decisions based on the collected data.

[0087] The SSH (Secure Shell) security protocol is used to visualize the data in real time. It is a protocol whose function is to offer remote access to a server, the main peculiarity is that this access is secure, since all the information is encrypted. This prevents it from being leaked and a third party from being able to see that data.

[0088] It is one of the most secure protocols for remote connection to a server. It is available for Linux and macOS, in addition to being able to use a client on Windows. Basically, it consists of being able to manage a server remotely, but also to do it securely.

[0089] SSH uses an authentication system, providing security to the communication, for example, it is used to enter a computer remotely and use a username and password.

[0090] SSH is based on 128-bit encryption, which guarantees strong protection and makes it really difficult for an intruder to decrypt and read the data being sent or received.

[0091] This protocol allows:

[0092] Updating a device or making changes

[0093] Modify or copy files

[0094] One advantage of the SSH protocol is the secure transfer of files between the host and the server. There are two ways to encrypt the data. These are symmetric and asymmetric encryption.Symmetric Encryption.

[0095] In this form a key is used, which is secret. Its function is to encrypt and in turn decrypt the contents of a message for the client and the host. Therefore, anyone who has such a key can view the content. It is also known as shared key or shared secret encryption. It may seem that this is a non-secure mechanism, but the opposite is true, since the key is not transmitted between the client and the host. Instead, the two teams share public data and then manipulate it to perform an independent calculation that results in the secret key.Asymmetric Encryption.

[0096] This case is the opposite of the previous one, and not only because of the name. Two keys are used here, one public and one private. These form what is called a key pair. First, the public key is distributed among computers in an open way. Being a key that can be calculated as we saw in the previous case. Then we have the private key, which always remains private, and is what makes this connection more secure. Therefore, no third party can know about it.

[0097] In order to determine the INPT, international and local standards are taken as a reference base, which are the result of Benchmarking carried out with the companies IHS Markit and Wood Mackenzie in more than 5000 wells worldwide, representing the analysis of the data obtained from the operations monitored in the region, which are under constant revision as new data sets are captured and analyzed; These Key Performance Indicators (KPI) are presented as a reference in FIG. 2 and will serve as metrics for the implementation of the system, i.e., when the times of each executed activity exceeds the limits of the KPI standards defined and configured, the system is able to determine the existence of NPT (Non Productive Times) and INPT (Invisible Non-productive Times) during the drilling and completion activity of the oil well.

[0098] For the system to be able to determine the existence of NPT (Non Productive Times) and INPT (Invisible Non-productive Times), it requires data that are collected in different ways in the facility, and then combined and processed by means of the Drillit tool, executed in the server (5), these required processed data are: the platform state and the operation configuration, which are obtained in the following way.Platform State

[0099] The platform state is a combination of results between user input, readings from the WITS server (4) and calculations performed through the Drillit server processor configuration (5).

[0100] The platform state is calculated by means of three elements:

[0101] Last Reading. Refers to the last reading recorded by a sensor and stored in the WITS server database (4).

[0102] Real time. Refers to the real-time reading being detected by a sensor and recorded in the WITS server (4).

[0103] Threshold. Refers to the threshold value corresponding to each operation to be monitored.

[0104] FIG. 3 shows a flow chart indicating the process to obtain the platform states, in the first operation, the server (5) reads the configuration of the thresholds stored in the system, this configuration corresponds to a numerical value, called threshold, which is entered manually by the user in the server (5) for each of the variables to be evaluated.

[0105] Subsequently, in the WITS server (4), the last measurements recorded (last reading) by the plurality of sensors (2) located along the drilling architecture and stored in the database are read, and, finally, a new record is read in the WITS server (4) in real time through the plurality of sensors (2).

[0106] All collected and stored data are sent to the Drillit server (5) where the Drillit tool, when executed in the server processor (5), calculates the difference between the stored readings (Last Reading) and those recorded in real time (Real Time), then the value obtained from this difference is compared with respect to the threshold value entered by the user for the same variable, if the difference is greater or less than the threshold set, the Drillit tool will designate the state of the parameter as on / off (on / off). The purpose of this calculation is to be able to establish which elements of the drilling infrastructure are operating and under what conditions they are operating.

[0107] For example, as can be seen in FIG. 3, once the RPM (revolutions per minute) variable is extracted, the difference between the revolutions per minute in real time with respect to those of the previous measurement is calculated, if this difference is less than the threshold, the RPM on parameter is assigned, but if the difference is greater than the threshold, it is assigned to the RPM off parameter, and through these assigned states, it can be identified, for example, if the drill bit is rotating or static.

[0108] The same procedure is carried out for each variable, such as torque, SPP, flow, block position, bit depth and hook load.

[0109] As the on / off state representation is continuously monitored in real time, a mapping is generated to define the state of the platform.

[0110] Table 1 below is a representation of the data packets processed, indicating the on / off state for each of the variables.RPMTorqueSPPFlowBlockBit DepthSlipRigStaterpm-torque-ssp-flow-block-bitDepth-slip-Static_Off_Slipsoffoffoffoffstaticstaticoffrpm-torque-ssp-flow-block-bitDepth-slip-Rotating_Off_Slips_onoffoffonstaticstaticoffPumping_Onrpm-torque-ssp-flow-block-bitDepth-slip-Pumping_Off_Slipsoffoffoffonstaticstaticoffrpm-torque-ssp-flow-block-bitDepth-slip-Pipe_Move_Upoffoffoffoffupupoffrpm-torque-ssp-flow-block-bitDepth-slip-Pipe_Move_Downoffoffoffoffoffdownoffrpm-torque-ssp-flow-block-bitDepth-slip-Washing_Downonoffoffondowndownoffrpm-torque-ssp-flow-block-bitDepth-slip-Pumping_Outonoffoffonupupoffrpm-torque-ssp-flow-block-bitDepth-slip-Static_On_Slipsoffoffoffoffstaticstaticonrpm-torque-ssp-flow-block-bitDepth-slip-Pumping_On_Slipsonoffoffonstaticstaticonrpm-torque-ssp-flow-block-bitDepth-slip-Block_Down_On_Slipsoffoffoffoffdownstaticonrpm-torque-sspflow-block-bitDepth-slip-Rotating_On_Slipsonoffoffoffstaticstaticonrpm-torque-ssp-flow-block-bitDepth-slip-Rotating_On_Slipsononoffoffstaticstaticonrpm-torque-ssp-flow-block-bitDepth-slip-Static_On_Slipsoffoffoffoffstaticstaticonrpm-torque-ssp-flow-block-bitDepth-slip-Block_Up_On_Slipsoffoffoffoffupstaticonrpm-torque-ssp-flow-block-bitDepth-slip-Custon_Pattern_Aoffoffoffoffupuponrpm-torque-ssp-flow-block-bitDepth-slip-Custom_Pattern_Boffoffoffoffdowndownonrpm-torque-ssp-flow-block-bitDepth-slip-Pumping_On_Slips_Weak_onoffoffondowndownonPatternrpm-torque-ssp-flow-block-bitDepth-slip-Reaming_Up_Off_Slipsononononupupoffrpm-torque-ssp-flow-block-bitDepth-slip-Pumping_On_Slipsoffoffononstaticstaticonrpm-torque-ssp-flow-block-bitDepth-slip-Rotating_Off_Slips_ononoffoffstaticstaticoffPumping_Offrpm-torque-sspflow-block-bitDepth-slip-Pumping_Off_Slipsoffoffononstaticstaticoffrpm-torque-ssp-flow-block-bitDepth-slip-Reaming_Off_Slipsononononstaticstaticoffrpm-torque-ssp-flow-block-bitDepth-slip-Block_Down_On_Slipsononoffoffdownstaticonrpm-torque-ssp-flow-block-bitDepth-slip-Block_Up_On_Slipsononoffoffupstaticonrpm-torque-ssp-flow-block-bitDepth-slip-Block_Down_On_Slipsoffoffoffoffdownstaticoffrpm-torque-ssp-flow-block-bitDepth-slip-Block_Up_On_Slipsoffoffoffoffupstaticoffrpm-torque-ssp-flow-block-bitDepth-slip-Pipe_Move_Upononoffoffupupoffrpm-torque-ssp-flow-block-bitDepth-slip-Pipe_Move_Downononoffoffdowndownoffrpm-torque-ssp-flow-block-bitDepth-slip-Pipe_Move_Upoffoffononupupoffrpm-torque-ssp-flow-block-bitDepth-slip-Pipe_Move_Downoffoffonondowndownoffrpm-torque-ssp-flow-block-bitDepth-slip-Custom_Pattern_Aononononupuponrpm-torque-ssp-flow-block-bitDepth-slip-Custom_Pattern_Aoffoffononupuponrpm-torque-ssp-flow-block-bitDepth-slip-Custom_Pattern_Aononononupuponrpm-torque-ssp-flow-block-bitDepth-slip-Custom_Pattern_Coffoffonondowndownonrpm-torque-ssp-flow-block-bitDepth-slip-UNMAPPEDononononstaticstaticon

[0111] From the data shown, in the first line, when the state of RPM, torque, SPP, Flow and slip are off, and block, bit Depth are static, the platform state determined by the Drillit tool is: Static_Off_Slips.

[0112] And so, for each of the states, a code is generated that represents the operating state format of the platform and works for all the mapping of variables to states.Operating Configuration

[0113] It corresponds to the initial configuration of the system and is made up of values that the user registers through a standards interface included in the Drillit tool and shown in FIG. 4. The interface has five tabs corresponding to each of the operations to be configured, such as: drill pipe trip, drilling, casing, timing operation and production platform, through which, the user for each of the operations, configures its operation according to its standards, providing predetermined parameters corresponding to the metrics with respect to a target time corresponding to the performance according to the KPIs (FIG. 2).

[0114] Once the equipment evolves to new parameters for the KPIs, they can be updated in this interface.

[0115] FIG. 5 shows the process diagram for the automated monitoring of INPT in real time in drilling and completion operations for oil wells, where, as can be seen, by means of the platform state represented by a series of codes generated for each of the operations, shown in Table 1 and the operation configuration, the metric calculation is then carried out, this calculation is carried out by means of the Drillit tool, i.e., based on the current operation, type, drill bit state and platform state, a mapping is generated to the OperationStatus, used to define the time metrics, e.g., connection, pre-connection, etc., and which are exemplified in FIG. 6a.

[0116] In the same way as in the case of platform state, the metrics obtained are represented through codes, which the Drillit tool itself is capable of generating and which can be visualized in FIG. 6b.

[0117] Once the measurements are parameterized according to the same metrics, such as time (min / hours), the Drillit tool is configured to carry out a KPI evaluation process, which consists of comparing the calculated metrics, which are the result between the platform states and the operation configuration, with respect to those contained in the KPI standards, calculating speeds, connection times, application of standard limits to delimit times, as well as the difference between the time projected for the activity and the time actually executed, which corresponds to the result of the Invisible Non-productive Times (INPT), with which it is also possible to calculate the efficiency of the operation in relation to the KPIs, since the monitoring is performed in real time.

[0118] In other words, non-compliance with the KPIs due to the difference between the standards and the activities recorded generates the INPTs, resulting in the issuance of alerts.

[0119] When the speeds and times of each activity executed in real time exceed the standard KPI limits defined and configured in the system, Drillit displays color-coded performance to the user in the well.

[0120] Green: Less than or equal to the standard; is meeting the standard.

[0121] Yellow: It is between the standard limit and your configured percentile (P50, P60 or whichever you choose).

[0122] Orange: Less than or equal to the percentile plus 20%.

[0123] Red: Above the configured percentile plus 20%; poor performance.

[0124] With this easily identifiable color code, the user can take action in real time and apply improvement plans to try to meet the target times, or otherwise identify the loss of performance that is due to the condition of the tool that is used or is not working properly.

[0125] FIG. 7 is a representation of the real-time alert system, where, as explained above, the operations correspond to the activities to be performed during the drilling process and that are comparable with respect to the KPIs, these operations together with telemetry such as readings obtained through the plurality of sensors in real time, are sent to the WITS server (4) where they are stored and through the known processing, WITS data are generated, which in turn are sent to the server (5), where the Drillit tool makes the processor is configured to perform the INPT calculations taking all the data that have been processed and stored in the database of the processor.

[0126] Once the INPT calculation has been performed, the Drillit tool has the ability to provide a system of alerts, displays and reports.

[0127] When a INPT is determined in the event of non-compliance with the KPIs, the alert system generates a real-time alert, which can be visual, audible or a combination of both.

[0128] Visualizers are a user interface that allows the visualization of processed information from all connected platforms. This interface allows supervisors and operations managers to get an overview of the performance of multiple platforms and make informed decisions based on the data collected.

[0129] The visualization module uses data from the database to generate real-time indicators for different users. KPI visualizations are available through a public dashboard.

[0130] Data processed on local servers are replicated to a central server in the cloud, where advanced analysis is performed. This architecture allows for scalable analysis and centralized visualization of the information processed from all connected platforms.

[0131] Drillit also offers real-time automated reporting. This differential functionality allows users to obtain detailed and accurate information on the performance of oil well drilling operations immediately. These reports can include key metrics such as invisible non-productive time, operation efficiency, platform performance, among others.

[0132] Automated real-time reporting allows users to access valuable information quickly and efficiently, without the need for manual analysis or extensive data processing, and can be automated and customized to users' needs and preferences, providing specific and relevant information for decision making.

[0133] An important aspect of the INPT analysis of the present invention is the elaboration of comparative analysis of trends and behavior of the indicators:

[0134] By stages

[0135] Wells

[0136] Fields

[0137] Drilling equipment

[0138] Crews

[0139] Contract outlines

[0140] Comparative analyses of trends in invisible non-productive time indicators allow:

[0141] Identifying skills of crews and management personnel by company

[0142] Standardizing operational practices by capitalizing on the different experiences of personnel.

[0143] Identification of trends in the introduction of TR

[0144] Detect operating practices by company

[0145] The Drillit tool is developed in TypeScript, a programming language that optimizes data processing. This tool uses predefined metrics to compare the processed sensor data with established measurement standards. These metrics allow to evaluate how optimal an operation is executed based on the data collected. Using TypeScript, Drillit can perform accurate and efficient calculations to analyze and evaluate the performance of the drilling operation.

[0146] The functions described in the present specification may be stored on a processor-readable or computer-readable medium. The term “computer-readable medium” refers to any available medium that can be accessed by a computer or processor. By way of example, such a medium may comprise random access memory (RAM), read-only memory (ROM), electrically programmable read-only memory (EEPROM), flash memory, compact disk read-only memory (CD-ROM) or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the described tool, and which can be accessed by computer.

[0147] Having sufficiently described the invention, I consider as a novelty and therefore claim as my exclusive property, the contents of the following claims.

Claims

1. Processing system for automated real-time Invisible Non-productive Time (INPT) monitoring in drilling and completion operations for oil wells, comprising:a plurality of sensors located along the drilling infrastructure capable of obtaining data from drilling operations,a WITS server that receives and stores the data collected from the plurality of sensors using a connection to a TCP IP port using the WITS protocol,a server comprising a processor and a memory, in charge of carrying out the processing of data received by the WITS server and in communication with a router in charge of sending wirelessly the information of the calculated data to be displayed in the operator's cabin and an on-site display,an APN through which all the information that has been monitored and calculated is sent to the cloud and can be viewed in real time through unlimited web access to 24-hour monitoring centers comprising a plurality of screens and remote interfaces, as well as at external locations,Wherein the processor is configured for:calculating the platform state through the combination of results between a plurality of data inputs called thresholds, the reading of the last measurements recorded by the plurality of sensors, and the reading of a new record in the WITS server in real time through the plurality of sensors, wherein the value obtained between the difference of the stored readings and the recorded readings in real time is compared with respect to the threshold value for the same variable, if the difference is greater or less than the established threshold, the state of the parameter is designated as on / off for each of these variables, establishing a particular code for each of the platform states;determining the initial configuration of the system, which will be made up of values collected through the standards interface that represent the metrics with respect to a target time and correspond to the performance in terms of KPIs;calculating metrics by performing a mapping between the platform state and the operating configuration to define the timing metrics; andevaluating the metrics calculated with respect to the KPI standards, if it is determined that the speeds and times of each activity executed in real time exceed the KPI standard limits, through a color code its performance is established; where:Green: performance is less than or equal to the standard and the standard is being met;Yellow: the performance is at the standard limit and its configured percentile;Orange: performance is less than or equal to the percentile plus 20%.Red: performance is above the configured percentile plus 20% representing poor performance.

2. The processing system for automated real-time INPT monitoring in drilling and completion operations for oil wells according to claim 1, wherein once the processor evaluates the calculated metrics with respect to the KPI standards, it can generate automated reports including metrics such as INPT, operating efficiency and platform performance.

3. The processing system for automated real-time INPT monitoring in drilling and completion operations for oil wells according to claim 1, wherein once the processor evaluates the calculated metrics with respect to the KPI standards, it can generate visual, audible or a combination of both alerts indicating non-compliance with KPIs representing INPT.

4. The processing system for automated real-time INPT monitoring in drilling and completion operations for oil wells according to claim 1, wherein for real-time data visualization, the SSH security protocol is used.

5. A method of automated real-time INPT monitoring in a drilling and completion system for oil wells comprising:a plurality of sensors located along the drilling infrastructure capable of obtaining data from drilling operations in real time,a WITS server that receives and stores the data collected from the plurality of sensors using a connection to a TCP IP port using the WITS protocol,a server comprising a processor and a memory, in charge of carrying out the processing of data received by the WITS server and in communication with a router in charge of sending wirelessly the information of the calculated data to be displayed in the operator's cabin and in an on-site display,an APN through which all the information that has been monitored and calculated is sent to the cloud and can be viewed in real time through unlimited web access to 24-hour monitoring centers comprising a plurality of screens and remote interfaces, as well as at external locations,wherein the processor is configured to carry out the steps of the method:calculating the platform state through the combination of results between a plurality of data inputs called thresholds, the reading of the last measurements recorded by the plurality of sensors, and the reading of a new record in the WITS server in real time through the plurality of sensors, wherein the value obtained between the difference of the stored readings and the recorded readings in real time is compared with respect to the threshold value entered by the user for the same variable, if the difference is greater or less than the established threshold, the state of the parameter will be designated as on / off for each of these variables and will be identified through a code for each of them;determining the initial configuration of the system, which will be made up of values collected through the standards interface that represent the metrics with respect to a target time and correspond to the performance in terms of KP;calculating metrics by performing a mapping between the platform state and the operating configuration to define the timing metrics; andevaluating the metrics calculated with respect to the KPI standards, if it is determined that the speeds and times of each activity executed in real time exceed the KPI standard limits, through a color code its performance is established; where:Green: performance is less than or equal to the standard and the standard is being met;Yellow: the performance is at the standard limit and its configured percentile;Orange: performance is less than or equal to the percentile plus 20%.Red: performance is above the configured percentile plus 20% representing poor performance.

6. The method of automated real-time INPT monitoring in drilling and completion operations for oil wells according to claim 5, wherein once the calculated metrics are evaluated with respect to the KPI standards, the processor is configured to be able to generate automated reports that include metrics such as INPT, operating efficiency and platform performance.

7. The method of automated real-time INPT monitoring in drilling and completion operations for oil wells according to claim 5, wherein once the calculated metrics are evaluated against the KPI standards, the processor is configured to be able to generate visual, audible or a combination of both alerts indicating non-compliance with KPIs representing INPT.

8. The method of automated real-time INPT monitoring in drilling and completion operations for oil wells according to claim 5, wherein for real-time data visualization, the SSH security protocol is used.

9. Computer-readable medium capable of carrying out automated real-time INPT monitoring in a drilling and completion system for oil wells, wherein it carries out the method steps according to claim 5.

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